ergouzi-video-gen

Ergouzi Video Gen

Use this Skill as a thin adapter between Codex and the existing Ergouzi video API. Codex prepares the model input; the scripts only handle credentials, local file conversion, request submission, task polling, and result download.

Prerequisites

• Require Python 3.10 or newer and network access to https://ergouzi.life.
• Use the initialized user config by default. ERGOUZI_MEDIA_API_KEY and ERGOUZI_MEDIA_BASE_URL are explicit runtime overrides; generic ERGOUZI_API_KEY and ERGOUZI_BASE_URL are accepted when no config exists.
• If credentials are missing, ask the user to initialize them locally with python scripts/configure.py. Never ask the user to paste a key into chat.
• If the optional ergouzi-media-mcp Codex plugin is installed, prefer its check_configuration, list_models, get_model_schema, create_prediction, get_prediction, cancel_prediction, and download_prediction tools for the API lifecycle. Keep the Python runner as the fallback when the MCP tools are unavailable.
• Accept supported media as directly downloadable HTTPS URLs, data URIs, or local files that fit the existing 4 MiB JSON request limit: JPEG/PNG/WebP images, MP4 video, and FLAC/MP3/WAV audio. Use --image, --video, --audio, or --last-frame-image for common local-file workflows. In input JSON, put { "$local_file": "C:/path/media.ext" } in place of a media URL. The runner converts local files to data URIs; use an HTTPS URL when the expanded request would exceed the API limit.

Workflow

1. Submit a paid prediction only when the user explicitly asks to generate or transform a video.
2. Honor an explicit model choice. Otherwise let Codex select one of the four models from the task's required input/output capability; do not hide models or apply server-routing policy.
3. Read references/model-reference.md for the selected model's objective API contract. Use --prompt only for ergouzi/e-video; other models expose model-specific text fields through --input-file, --input-json, or stdin. Supply the complete model input object without the outer { "input": ... } envelope. Convenience arguments override the corresponding JSON fields. The runner resolves $local_file objects before submission and otherwise leaves input values unchanged. Prefer a UTF-8 JSON file for structured input across operating systems; files and stdin may include a UTF-8 BOM.
4. Prefer the MCP tools when available. Otherwise run scripts/run.py predict. Both paths create one logical task, reuse the same idempotency key for bounded transport retries, record the task_* ID, poll to a terminal state, and download successful outputs. If a submission is interrupted before the task ID is returned, retry the exact request with the printed --idempotency-key; do not start a new paid request with a new key.
5. Report the model, task ID, terminal status, and absolute saved paths.
6. If execution was interrupted or timed out, resume with status --wait --download. Do not create a replacement task unless the user explicitly asks.